BibTeX Export for Local Access to Huge Random Objects Through Partial Sampling

Copy to Clipboard Download

@InProceedings{biswas_et_al:LIPIcs.ITCS.2020.27,
  author =	{Biswas, Amartya Shankha and Rubinfeld, Ronitt and Yodpinyanee, Anak},
  title =	{{Local Access to Huge Random Objects Through Partial Sampling}},
  booktitle =	{11th Innovations in Theoretical Computer Science Conference (ITCS 2020)},
  pages =	{27:1--27:65},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-134-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{151},
  editor =	{Vidick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2020.27},
  URN =		{urn:nbn:de:0030-drops-117126},
  doi =		{10.4230/LIPIcs.ITCS.2020.27},
  annote =	{Keywords: sublinear time algorithms, random generation, local computation}
}

The metadata provided by Dagstuhl Publishing on its webpages, as well as their export formats (such as XML or BibTeX) available at our website, is released under the CC0 1.0 Public Domain Dedication license. That is, you are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data, even for commercial purposes, all without asking permission. Of course, we are always happy if you provide a link to us as the source of the data.

Read the full CC0 1.0 legal code for the exact terms that apply: https://creativecommons.org/publicdomain/zero/1.0/legalcode

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail